Michael L. Bynum Gabriel A. Hackebeil William E. Hart Carl D. Laird Bethany L. Nicholson John D. Siirola Jean-Paul Watson David L. Woodruff Bynum Pyomo — Optimization Modeling in Python

Pyomo — Optimization Modeling in Python

von Michael L. Bynum Gabriel A. Hackebeil William E. Hart Carl D. Laird Bethany L. Nicholson John D. Siirola Jean-Paul Watson David L. Woodruff

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Beschreibung

This book provides a complete and comprehensive guide to Pyomo (Python Optimization Modeling Objects) for beginning and advanced modelers, including students at the undergraduate and graduate levels, academic researchers, and practitioners. Using many examples to illustrate the different techniques useful for formulating models, this text beautifully elucidates the breadth of modeling capabilities that are supported by Pyomo and its handling of complex real-world applications. In the third edition, much of the material has been reorganized, new examples have been added, and a new chapter has been added describing how modelers can improve the performance of their models.  The authors have also modified their recommended method for importing Pyomo. A big change in this edition is the emphasis of concrete models, which provide fewer restrictions on the specification and use of Pyomo models. 

Pyomo is an open source software package for formulating and solving large-scale optimization problems. The software extends the modeling approach supported by modern AML (Algebraic Modeling Language) tools. Pyomo is a flexible, extensible, and portable AML that is embedded in Python, a full-featured scripting language. Python is a powerful and dynamic programming language that has a very clear, readable syntax and intuitive object orientation. Pyomo includes Python classes for defining sparse sets, parameters, and variables, which can be used to formulate algebraic expressions that define objectives and constraints. Moreover, Pyomo can be used from a command-line interface and within Python's interactive command environment, which makes it easy to create Pyomo models, apply a variety of optimizers, and examine solutions.

Review of the Second edition:

This book provides a detailed guide to Pyomo for beginners and advanced users from undergraduate students to academic researchers to practitioners. … the book is a good software guide which I strongly recommend to anybody interested in looking for an alternative to commercial modeling languages in general or in learning or intensifying their Pyomo skills in particular.

—Christina Schenk, SIAM Review, Vol. 61 (1), March 2019

 


This book provides a complete and comprehensive guide to Pyomo (Python Optimization Modeling Objects) for beginning and advanced modelers, including students at the undergraduate and graduate levels, academic researchers, and practitioners. Using many examples to illustrate the different techniques useful for formulating models, this text beautifully elucidates the breadth of modeling capabilities that are supported by Pyomo and its handling of complex real-world applications. In the third edition, much of the material has been reorganized, new examples have been added, and a new chapter has been added describing how modelers can improve the performance of their models.  The authors have also modified their recommended method for importing Pyomo. A big change in this edition is the emphasis of concrete models, which provide fewer restrictions on the specification and use of Pyomo models. 

Pyomo is an open source software package for formulating and solving large-scale optimization problems. The software extends the modeling approach supported by modern AML (Algebraic Modeling Language) tools. Pyomo is a flexible, extensible, and portable AML that is embedded in Python, a full-featured scripting language. Python is a powerful and dynamic programming language that has a very clear, readable syntax and intuitive object orientation. Pyomo includes Python classes for defining sparse sets, parameters, and variables, which can be used to formulate algebraic expressions that define objectives and constraints. Moreover, Pyomo can be used from a command-line interface and within Python's interactive command environment, which makes it easy to create Pyomo models, apply a variety of optimizers, and examine solutions.


Third edition has been reoganized to provide better information flow for readers who are either new or experienced Pyomo users Unique book describing the user-friendly Pyomo modeling tool, the most comprehensive open source modeling software that can model linear programs, integer programs, nonlinear programs, stochastic programs and disjunctive programs Discusses Pyomo's modeling components, illustrated with extensive examples Introduces beginners to the software and presents chapters for advanced modeling capabilities? Contains a comprehensive tutorial Includes supplementary material: sn.pub/extras

Autor*in

Michael L. Bynum

Themen in »Pyomo — Optimization Modeling in Python«

Pyomo modeling library Python optimization modeling and simulation mathematical modeling tool algebraic modeling languages Python script Python data hybrid optimization Matplotlib NumPy SciPy PySP Pyomo tutorial

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Details

ISBN: 9783030689285
Verlag: Springer International Publishing
Erscheinung: 30.03.2021

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